A novel damage detection method based on sequential iteration and Gaussian mixture model for structural health monitoring under environmental effects.

Environmental effects often cause variability in dynamic features, obscuring actual damage indicators and leading to false alarms in damage detection. The Gaussian mixture model (GMM) based method is an effective solution, but challenges such as selecting initial model parameters and determining the optimal number of Gaussian components can hinder its performance. To address these challenges, we propose a two-step method that combines sequential iteration with the GMM approach.